41078 Computing Science Studio 1
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Credit points: 6 cp
Subject level:
Undergraduate
Result type: Grade and marksRequisite(s): 36 credit points of completed study in spk(s): C09119 Bachelor of Computing Science (Honours)
Recommended studies:
completion of first-year Bachelor of Computing Science (Honours) subjects
Description
Research is the engine for innovation and development of our society. This studio subject aims to bring students into the amazing world of computer science research. The subject explores the meaning of research, the reasons for research, and research strategies and tools in the information age. Students are trained on academic writing for literature review in academic publications and project reports. Moreover, they discuss research collaboration, leadership, and research ethics. Students identify the topics that they are interested and practice their learned knowledge to investigate their selected topics under the mentorship of the teaching team. They are also encouraged to seek advice from the UTS leading computer scientists. Students focus on skill development for their careers in computing science – developing the communication skills necessary for academic and professional communication, the ethical principles required of modern IT professionals, and the analytical skills needed for the critical use of academic literature.
Subject learning objectives (SLOs)
Upon successful completion of this subject students should be able to:
| 1. | Identify the social and ethical impacts of computer science research in a given context. (B.1) |
|---|---|
| 2. | Design a methodological solution to systematically review a research field/topic. (C.1) |
| 3. | Implement a set of analytical methods, tools, and strategies to analyse and evaluate academic resources. (D.1) |
| 4. | Construct written, spoken, and visual communication with teamwork. (E.1) |
| 5. | Reflect self-development, learning experience, and collaborative interactions. (F.1) |
Course intended learning outcomes (CILOs)
This subject also contributes specifically to the development of the following Course Intended Learning Outcomes (CILOs):
- Socially Responsible: FEIT graduates identify, engage, interpret and analyse stakeholder needs and cultural perspectives, establish priorities and goals, and identify constraints, uncertainties and risks (social, ethical, cultural, legislative, environmental, economics etc.) to define the system requirements. (B.1)
- Design Oriented: FEIT graduates apply problem solving, design and decision-making methodologies to develop components, systems and processes to meet specified requirements. (C.1)
- Technically Proficient: FEIT graduates apply abstraction, mathematics and discipline fundamentals, software, tools and techniques to evaluate, implement and operate systems. (D.1)
- Collaborative and Communicative: FEIT graduates work as an effective member or leader of diverse teams, communicating effectively and operating within cross-disciplinary and cross-cultural contexts in the workplace. (E.1)
- Reflective: FEIT graduates critically self-review their performance to improve themselves, their teams, and the broader community and society. (F.1)
Teaching and learning strategies
This subject is a studio-based learning experience. Given the persona of a professional computer scientist, students are trained with a comprehensive skillset of research essentials, academic writing, and knowledge of success in research through an iterative learning process. In a collaborative environment, the studio follows the Agile methodology, meaning the semester is organised into 4 sprints and students work together towards a project that investigates a specific topic in field of computer science.
This subject consists of 12 weekly 3-hour workshops, with a combinative mode of self-paced learning/research and weekly face-to-face workshops. Students work as a team with 4-5 members sharing similar research interests (e.g., the same discipline) and with complementary skillsets and diverse team responsibilities. With three stages across the initiative, progress, and solution of a project, each team is required to plan, design, develop, and deliver their solutions. During the workshops, students will receive in-time guiding feedback from the teaching team, as well as possible consultation support and advice from UTS academic researchers in relevant disciplines. These workshops will bring valuable opportunities for students to establish their knowledge base on the broad computer science discipline and deepen their understanding of specific downstream topics and techniques.
Content (topics)
- Research Essentials
- Academic Writing
- Success in Research
Assessment
Assessment task 1: Portfolio and Presentations
| Intent: | To document the iterative learning process and artefacts that demonstrate the achievement of learning goals related to computing science. |
|---|---|
| Objective(s): | This assessment task addresses the following subject learning objectives (SLOs): 1, 2, 3, 4 and 5 This assessment task contributes to the development of the following Course Intended Learning Outcomes (CILOs): B.1, C.1, D.1, E.1 and F.1 |
| Type: | Portfolio |
| Groupwork: | Group, individually assessed |
| Weight: | 100% |
| Length: | 6000 words |
Minimum requirements
In order to pass the subject, a student must achieve an overall mark of 50% or more.
References
APA Referencing: https://www.lib.uts.edu.au/referencing/apa
Brick, J., Herke, M., & Wong, D. (2016). Academic culture: A student’s guide to studying at university (3rd ed.). Sydney: Macmillan Science & Education.
Jones, B. F. (2021). The rise of research teams: Benefits and costs in economics. Journal of Economic Perspectives, 35(2), 191-216.
Liebowitz, J., Agresti, W., & Djavanshir, G. R. (2005). Communicating as IT professionals. Upper Saddle River: Pearson Prentice Hall.
Meltzoff, J., & Cooper, H. (2017). Critical thinking about research: Psychology and related fields (2nd ed.). American Psychological Association.
Morley-Warner, T. (2014). Academic writing is...: A guide to writing in a university context. Sydney: Sydney University Press.
Zhang, Y., Wu, M., Tian, G. Y., Zhang, G., & Lu, J. (2021). Ethics and privacy of artificial intelligence: Understandings from bibliometrics. Knowledge-Based Systems, 222, 106994.
Zobel, J. (2014). Writing for computer science (3rd ed.). London: Springer-Verlag.